A modern cross-platform, responsive Human-Machine Interface (HMI) designed for real-time monitoring, historical data analysis, and control of a research-grade geothermal power plant in Taiwan. It leverages the Total Flow cycle to extract energy directly from the two-phase geothermal fluid.
- Frontend deployed on Cloudflare Pages: https://scada.hanl.in/
- Backend deployed on Oracle Cloud Infrastructure
- SCADA/IoT Human Machine Interface (HMI)
The primary goal of this project is to develop and deploy a flexible, developer-friendly, and modern monitoring and control system tailored for a research-grade geothermal power plant and facilitate research and analysis. Key features include:
- Real-time insights into key operational parameters such as well enthalpy, thermal efficiency, fluid temperature, pipe pressure, mass flow rate, and power generation metrics.
- Efficient data acquisition, processing, logging for >100 sensors at ~1 sec resolution.
- High-performance data visualization system for historical data analysis capable of visualizing large datasets with >1 billion data points.
- Implement remote control capabilities for essential plant components.
- Record and display on-site imaging from IP cameras.
- Integration of diverse hardware components using industrial communication protocols.
- A user-friendly remote supervisory control and monitoring via a modern responsive web-based interface with support for phones, tablets, laptops, desktops to huge TV monitors.
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Cost-Effectiveness:
- Aims to reduce engineering time and hardware costs compared to traditional proprietary DCS/SCADA solutions.
- Unified JavaScript language across the stack enables flexible placement of logic on the edge, server or client, and simplifies hiring.
- Leverages open-source software components, minimizing licensing fees.
- Utilizes readily available and cost-effective hardware as PLCs (Raspberry Pi, Arduino).
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Real-time Monitoring & Control:
- Web and mobile dashboards for real-time data visualization.
- Interactive charts for historical data discovery and analysis.
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Modular & Scalable Architecture:
- Supports a diverse range of sensors (Temperature: PT100; Pressure: Absolute/Gauge; Flow: Magnetic, Coriolis, Vortex; Power: V, I, Freq, PF; Speed: Optical, Hall; pH; Environmental, etc.).
- Interfaces with various actuators and alarms.
- Horizontally scalable using containerized systems.
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Data Acquisition & Management:
- Time-series database (MongoDB) optimized for high-frequency sensor data logging.
- Comprehensive logging with filtering capabilities.
- Data export for offline analysis (e.g., CSV, JSON).
- Historical trend analysis and reporting tools.
- No data loss even when working with a unreliable 4G connection.
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Remote Access & Security:
- JWT based authentication and authorization for users and plc.
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Open Standards & Protocols:
- Modbus-RTU (RS-485) for robust industrial device communication.
- REST/WebSocket APIs for seamless frontend/backend integration and third-party access.
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Cross-Platform Compatibility:
- Web interfaces compatible with modern browsers (Chrome, Firefox, Safari, Edge).
- Progressive Web Apps (PWA) for Android and iOS devices.
- Backend runs on standard server environments (Linux, Windows, macOS).
The system employs a distributed architecture leveraging modern IoT principles combined with traditional SCADA protocols:
Software-defined PLC (scada-iot-plc)
- Description: Node.js application designed to run on edge hardware (like Raspberry Pi) functioning as a Programmable Logic Controller.
- Responsibilities: Direct communication with field devices via MODBUS, real-time data acquisition, execution of control loops, data preprocessing, and communication with the central Supervisor.
Horizontally Scalable Supervisor (scada-iot-supervisor)
- Description: Central backend system built with Node.js and FeathersJS.
- Responsibilities: Aggregating data from multiple PLCs, managing the MongoDB database for time-series data and configuration, providing real-time updates via WebSockets, offering a REST API, handling user authentication, and orchestrating system-wide logic.
Modern Responsive HMI (scada-iot-hmi)
- Description: Frontend application built with VueJS and Quasar Framework, functioning as a Progressive Web App (PWA).
- Responsibilities: Providing the user interface for real-time data visualization, displaying system status, offering interactive charts for historical data analysis, allowing remote control actions, and managing user sessions.
- Edge Controller: Raspberry Pi serves as the main processing unit.
- Remote Terminal Units (RTUs): Industrial controllers interfacing with field devices.
- Sensors: Temperature (RTD PT100), Pressure (Danfoss MBS 3000), Electromagnetic Flowmeters (BMS, LDG), Coriolis Flowmeters (E+H, Micro Motion), Vortex Flowmeters (MIK-LUGB), pH Meters, Optical/Hall Effect RPM Sensors, Electrical (Voltage, Current, Frequency, Power), etc.
- Actuators: Valves, Alarms, and Inverters (ABB PVI-12.5-TL-OUTD).
- Networking: Ethernet Switches, WiFi Access Points, 4G/LTE Routers, USB-to-RS485/232 Converters.
- Cameras: IP Cameras with on-site NAS recording.
- Power: Mean Well Power Supplies (24VDC, 12VDC, 5VDC).
- Analysis Tools: Hioki Power Analyzers, FLIR Thermal Cameras, High-Speed Cameras.
- Backend / PLC: Node.js, FeathersJS (Supervisor)
- Frontend: VueJS, Quasar Framework, Highcharts
- Database: MongoDB
- Message Queue: RabbitMQ (AMQP)
- Real-time Communication: WebSockets (TCP/IP)
- Industrial Communication: MODBUS RTU (RS-485)
- Hardware Platform (Edge): Raspberry Pi OS / Linux
- Process Management: PM2
- Web Server/Proxy: Nginx
- MODBUS-RTU: Used for robust communication with RTUs and other industrial devices connected to the custom I/O modules or directly.
- WebSockets: Enables real-time, bidirectional communication between the Node.js backend, the supervisory control system, and the user interface (UI).
This system was instrumental in the development and testing of a Total Flow geothermal power generation unit:
- Monitored Parameters: Wellhead pressure/temperature, flow rates (total, steam, brine), turbine inlet/outlet conditions, generator output (Voltage, Current, Frequency, Power Factor, kW, kVA), vibration, cooling system parameters, pH, ambient conditions.
- Control: Valve positioning for flow regulation, generator load control (via load banks or grid-tie inverters), emergency shutdown sequences.
- Data Logging: Captured high-frequency data during various test phases (load bank testing, grid synchronization trials) for performance analysis (e.g., Power vs. Pressure Drop curves, efficiency calculations).
- Remote Operation: Enabled remote monitoring of the unmanned test site via web dashboards and live camera feeds.
- Node.js: Version 18+ recommended (check individual subproject
package.jsonengines if specified). - npm: Version 8+ recommended (comes with Node.js).
- Git: For cloning the repository.
- MongoDB: A running instance accessible by the
scada-iot-supervisorbackend.
- NHR5200: Temperature and pressure sensors
- DW8/DW9: Power meters
- NHR3800: Frequency meters
- NHR3500: Advanced power quality analyzers
- GPE: Mass flow meters
- SINLDG: Magnetic Flow meters
- Supmea LMAG: Magnetic Flow meters
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Clone the repository:
git clone https://github.com/hotdogee/scada-iot-hmi.git cd scada-iot-hmi -
Install dependencies:
npm install
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Run the development server: (with hot-reloading)
npm run dev
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Build for production:
npm run build
This creates an optimized build in the
dist/directory.
This project is licensed under the MIT License - see the LICENSE file for details.
- Lanyang Geothermal Corp.
- Lead Developer: Han Lin hotdogee@gmail.com (https://github.com/hotdogee)
